Aparna Nathan

Efficient genome-wide mapping of reproducible, context-dependent eQTLs at single-cell resolution

The paper introduces Dynema, a method for genome-wide mapping of context-dependent and independent eQTLs at single-cell resolution, showing improved detection compared to pseudobulking approaches.

Reproducible single cell annotation of programs underlying T-cell subsets, activation states, and functions

The paper introduces TCAT, a pipeline to annotate T-cell GEPs, identifying 46 reproducible programs across diverse tissues and diseases.

Granzyme K drives a newly-intentified pathway of complement activation

This study identifies granzyme K as a driver of a novel complement activation pathway independent of classical, lectin, or alternative pathways.

Identifying genetic variants that influence the abundance of cell states in single-cell data

The paper introduces GeNA, a tool to identify genetic variants influencing cell state abundance in single-cell data, finding five loci associated with immune cell state shifts.

Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles

The paper develops SCENT, a method to create cell-type-specific enhancer-gene maps from single-cell multimodal data, identifying causal variants and genes for diseases.

Defining the function of disease variants with CRISPR editing and multimodal single cell sequencing

The paper uses CRISPR editing and multimodal single-cell sequencing to identify the functional effects of disease variants in primary human cells.

Modeling heterogeneity in single-cell perturbation states enhances detection of response eQTLs

The paper demonstrates that modeling single-cell perturbation states improves detection of reQTLs by accounting for cell-level heterogeneity in perturbation responses.

High-dimensional phenotyping to define the genetic basis of cellular morphology

This study identifies genetic variants associated with cellular morphology using high-content imaging and genomic data from iPSCs.

Mapping the dynamic genetic regulatory architecture of HLA genes at single-cell resolution

The paper maps cell-type-specific eQTLs for HLA genes across multiple tissues and identifies dynamic regulation of HLA-DQ genes in immune cells.

Immunosuppression causes dynamic changes in expression QTLs in psoriatic skin

This study identifies eQTLs in psoriatic skin that are modulated by local inflammation, showing that gene regulation is primarily influenced by skin-specific factors rather than systemic variables.

Dynamic regulatory elements in single-cell multimodal data capture autoimmune disease heritability and implicate key immune cell states

Cellular deconstruction of inflamed synovium defines diverse inflammatory phenotypes in rheumatoid arthritis

The paper deconstructs RA synovium using single-cell data to identify six cell type abundance phenotypes associated with distinct inflammatory states.

Efficient and precise single-cell reference atlas mapping with Symphony

Symphony maps query cells to large reference atlases efficiently, enabling rapid identification of cell states and phenotypes across diverse datasets.

Modeling memory T cell states at single-cell resolution identifies in vivo state-dependence of eQTLs influencing disease

The paper identifies state-dependent eQTLs in memory T cells by analyzing single-cell RNA and protein data from Peruvians, showing that gene regulation varies with cell states and disease-associated variants are enriched in these contexts.

IFN-γ and TNF-α drive a CXCL10+ CCL2+ macrophage phenotype expanded in severe COVID-19 and other diseases with tissue inflammation

The paper identifies a common inflammatory macrophage phenotype across severe COVID-19 and other inflammatory diseases, driven by IFN-γ and TNF-α, and suggests potential therapeutic targets.

Axes of inter-sample variability among transcriptional neighborhoods reveal disease associated cell states in single-cell data

This paper introduces CNA, a method to identify disease-associated cell states by analyzing transcriptional neighborhoods across samples, showing improved performance over cluster-based approaches in simulations and real datasets.

Deep transcriptome sequencing of subgenual anterior cingulate cortex reveals disorder-specific expression changes in major psychiatric disorders

The paper uses deep RNA sequencing to compare gene expression in the subgenual anterior cingulate cortex across major psychiatric disorders and controls, finding disorder-specific expression changes and genetic associations.

Maximizing statistical power to detect clinically associated cell states with scPOST

The paper introduces scPOST, a tool for estimating statistical power in single-cell studies, and shows that larger sample sizes, reduced batch effects, and lower cell state variability increase power to detect clinically associated cell state shifts.

Presto scales Wilcoxon and auROC analyses to millions of observations

One-versus-all rank-sum across 10 groups and 1,000 features on a sparse 1-million-observation simulation finished in 17 seconds instead of 6.4 hours, with the same pass yielding auROC.